Optimal cancer therapy is designed to exert maximal effect on tumor cells while having minimal side-effects on normal cells. Unfortunately this goal is difficult to achieve due to a lack of specificity for the cancer cells. Remarkable advances in our understanding of the molecular biology of cancer has provided possible avenues for more successful 'targeted' cancer treatment. Several crucial protein-protein and protein-RNA interactions occur exclusively in tumor cells and thus provide ideal targets for intervention. The proposed project is to develop a model system to target specific therapy of human breast cancer cells. We have chosen to target the interaction between the RNA subunit of telomerase (hTR) with three different proteins: i) the catalytic subunit of telomerase (hTERT), (ii) L22, one of two recently described hTR RNA-binding proteins and (iii) Staufen, the second of the recently identified hTR binding proteins. Telomerase is an excellent target as it is over-expressed in the majority of breast cancers. A genetic selection will be used to identify random, constrained peptide sequences that are capable of blocking this interaction specifically. This technique termed reverse three-hybrid screening allows one to select for specific blockers of known interactions in yeast cells. This procedure will be most suitable for high through-put drug screening projects since plasmids encoding, candidate blockers can be readily rescued and tested in mammalian bioassays. This technique will be applied to the screening of random peptide libraries and peptide libraries derived from natural sources. The validity of this approach will be established by measuring the efficacy of selected peptide inhibitors in inhibiting telomerase activity and the growth of breast cancer cells.